The mathematics of nonlinear programming
The mathematics of nonlinear programming
Performance Guarantees for Web Server End-Systems: A Control-Theoretical Approach
IEEE Transactions on Parallel and Distributed Systems
Self-Tuning Systems: Control and Signal Processing
Self-Tuning Systems: Control and Signal Processing
Real Time Optimization by Extremum Seeking Control
Real Time Optimization by Extremum Seeking Control
GridDB: a relational interface for the grid
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Applying Database Support for Large Scale Data Driven Science in Distributed Environments
GRID '03 Proceedings of the 4th International Workshop on Grid Computing
Self-Managing Systems: A Control Theory Foundation
ECBS '05 Proceedings of the 12th IEEE International Conference and Workshops on Engineering of Computer-Based Systems
The design and implementation of Grid database services in OGSA-DAI: Research Articles
Concurrency and Computation: Practice & Experience - Grid Performance
Feedback Utilization Control in Distributed Real-Time Systems with End-to-End Tasks
IEEE Transactions on Parallel and Distributed Systems
A novel approach to resource scheduling for parallel query processing on computational grids
Distributed and Parallel Databases
Query optimization over web services
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Online response time optimization of Apache web server
IWQoS'03 Proceedings of the 11th international conference on Quality of service
Adapting to changing resource performance in grid query processing
DMG 2005 Proceedings of the First VLDB conference on Data Management in Grids
A control theoretical approach to self-optimizing block transfer in Web service grids
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
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Nowadays, Web Services (WSs) play an increasingly important role in Web data management solutions, since they offer a practical solution for accessing and manipulating data sources spanning administrative domains. Nevertheless, they are notoriously slow and transferring large data volumes across WSs becomes the main bottleneck in such WS-based applications. This paper deals with the problem of minimizing at runtime, in a self-managing way, the datatransfer cost of a WS encapsulating a data source. To reducethe transfer cost, the data volume is typically divided intoblocks. In this case, response time exhibits a quadratic-like, non-linear behavior with regards to the block size; as such, minimizing the transfer cost entails finding the optimum block size. This situation is encountered in several systems, such as WS Management Systems (WSMSs) for DBMS-like data management over wide area service-based networks, and WSs for accessing and integrating traditional DBMSs. The main challenges in this problem include (i) the unavailability of an analytical model; (ii) the presence of noise, which incurs local minima; (iii) the volatility of the environment, which results into a moving optimum operating point; and (iv) the requirements for fast convergence to the optimal size of the request from the side of the client rather than of the server, and for low overshooting. This paper presents two novel solutions for detecting the optimum block size during data transmission, thus yielding lower response times. The solutions are inspired by the broader areas of runtime optimization and switching extremum control. They incorporate heuristics to avoid local optimal points, and address all the afore-mentioned challenges. The effectiveness andeffciency of the solutions is verified through empirical evaluation in real cases.